Juliana Wang

How can improved control of quantum tunneling in superconducting qubits outperform current coherence-preservation techniques?

Started Oct. 3, 2024

Abstract or project description

Quantum computing holds immense potential to revolutionize fields such as cryptography, optimization, and materials science by solving problems that are currently intractable for classical systems. A key challenge, however, lies in maintaining quantum coherence. In superconducting quantum systems, coherence is limited by noise, material imperfections, and quantum decoherence processes. This project investigates whether improved control over quantum tunneling can offer enhanced coherence times compared to existing preservation techniques or computing structures. By analyzing current superconducting qubit architectures and exploring tunneling-based design strategies, this study aims to identify more robust, scalable approaches to stabilizing quantum information and extending the functional reliability of quantum computers, allowing for its effective application across industries in the future.

Using Machine Learning For Exoplanet Classification

Started Aug. 10, 2023

Abstract or project description

Abstract With aims of discovering potential candidates and using that new found information to analyze the composition of the world as we know now, many efforts have been placed in to conduct research efficiently and accurately. With multiple methods for exoplanet detection such as shadow searching, the data produced from these methods still require interpretation to reach a conclusion (e.g. is there a dip in the light curve? ), which is why machine learning has recently come into the scene of astronomy with its potential to be trained for image classification tasks, requiring only a couple of seconds to a couple of minutes to complete their task. This paper used Convolutional Neural Networks (CNN), a type of Machine Learning specifically designed to classify images, and achieved a curve with an area-under-curve coverage of 0.91.